📚 PersonaLearn – Personalized Learning Management System

PersonaLearn is an AI-powered web-based Learning Management System (LMS) that offers customized learning experiences using student data and intelligent recommendations. The system is built with an integrated recommendation engine powered by machine learning to personalize content for every learner.

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🌐 Technologies Used

Layer	Technologies
Frontend	HTML, CSS, JavaScript, Tailwind CSS
Backend	PHP, Python, Python Libraries, TensorFlow, XAMPP
Database	MySQL, XAMPP

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🔍 Key Features

• 🎯 Personalized course recommendations based on learner history and performance
• 📈 Progress tracking dashboard with learning analytics
• 🔐 User authentication (Student & Admin roles)
• 📝 Course creation and enrollment system
• 💬 Discussion module for peer interaction
• 📊 Quiz and assessment support

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🤖 AI Recommendation Engine

The system uses Python and TensorFlow for:

• Generating learning paths
• Recommending relevant materials based on performance and interests
• Evaluating past behavior and quiz scores for continuous adaptation

Techniques used:

• Content-based filtering
• Performance-based adaptation
• TensorFlow model inference (classification/ranking logic)

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🖼️ Screenshots

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🚀 How to Run the Project Locally

1. Clone the Repository

git clone https://github.com/RohithaAiswarya16/Personalized-Learning-Management-System.git
cd Personalized-Learning-Management-System

2. Setup Backend (PHP + MySQL)

• Open XAMPP and start Apache and MySQL
• Move the project to your htdocs folder (e.g., C:/xampp/htdocs/PersonaLearn)
• Import the database:
  • Open http://localhost/phpmyadmin
  • Create a new database (e.g., personadb)
  • Import the .sql file provided in the repo

3. Run the Python ML Script (if separate)

If the recommendation system runs separately:

cd recommender
python recommender.py

4. Access the App

Open your browser and go to:

http://localhost/PersonaLearn

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📁 Project Structure

├── assets/                     # Images and screenshots
├── recommender/               # Python ML logic (TensorFlow, etc.)
├── php/                       # PHP files (frontend/backend logic)
├── css/                       # Tailwind/Custom CSS
├── js/                        # JavaScript scripts
├── database/                  # SQL dumps and structure
├── README.md
└── ...

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📈 Future Enhancements

• Add role-based dashboards for instructors
• Use NLP for content understanding and summarization
• Gamify learning with badges and rewards
• REST API integration between PHP and Python layer

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👩‍💻 Author

Rohitha Aiswarya
BTech CSE | AI/ML & Full Stack Enthusiast
GitHub: @RohithaAiswarya16

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⭐ Show Your Support

If you liked this project, please ⭐ the repository and share it with others!

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📜 License

This project is licensed under the MIT License.